githubmirror/julia

base/threadingconstructs.jl
464 строки16 KB
Ian Butterworth
Add note about `@threads` threadpool (#59802)
30 янв 2026, 02:58
30 янв 2026, 02:583688cec
# This file is a part of Julia. License is MIT: https://julialang.org/license

export threadid, nthreads, @threads, @spawn,
       threadpool, nthreadpools

"""
    Threads.threadid() -> Int

Get the ID number of the current thread of execution. The master thread has
ID `1`.

# Examples
```julia-repl
julia> Threads.threadid()
1

julia> Threads.@threads for i in 1:4
          println(Threads.threadid())
       end
4
2
5
4
```

!!! note
    The thread that a task runs on may change if the task yields, which is known as [`Task Migration`](@ref man-task-migration).
    For this reason in most cases it is not safe to use `threadid()` to index into, say, a vector of buffer or stateful objects.

"""
threadid() = Int(ccall(:jl_threadid, Int16, ())+1)

# lower bound on the largest threadid()
"""
    Threads.maxthreadid() -> Int

Get a lower bound on the number of threads (across all thread pools) available
to the Julia process, with atomic-acquire semantics. The result will always be
greater than or equal to [`threadid()`](@ref) as well as `threadid(task)` for
any task you were able to observe before calling `maxthreadid`.
"""
maxthreadid() = Int(Core.Intrinsics.atomic_pointerref(cglobal(:jl_n_threads, Cint), :acquire))

"""
    Threads.nthreads(:default | :interactive) -> Int

Get the current number of threads within the specified thread pool. The threads in `:interactive`
have id numbers `1:nthreads(:interactive)`, and the threads in `:default` have id numbers in
`nthreads(:interactive) .+ (1:nthreads(:default))`.

See also `BLAS.get_num_threads` and `BLAS.set_num_threads` in the [`LinearAlgebra`](@ref
man-linalg) standard library, and `nprocs()` in the [`Distributed`](@ref man-distributed)
standard library and [`Threads.maxthreadid()`](@ref).
"""
nthreads(pool::Symbol) = threadpoolsize(pool)

function _nthreads_in_pool(tpid::Int8)
    p = unsafe_load(cglobal(:jl_n_threads_per_pool, Ptr{Cint}))
    return Int(unsafe_load(p, tpid + 1))
end

function _tpid_to_sym(tpid::Int8)
    if tpid == 0
        return :interactive
    elseif tpid == 1
        return :default
    elseif tpid == -1
        return :foreign
    else
        throw(ArgumentError("Unrecognized threadpool id $tpid"))
    end
end

function _sym_to_tpid(tp::Symbol)
    if tp === :interactive
        return Int8(0)
    elseif tp === :default
        return Int8(1)
    elseif tp == :foreign
        return Int8(-1)
    else
        throw(ArgumentError("Unrecognized threadpool name `$(repr(tp))`"))
    end
end

"""
    Threads.threadpool(tid = threadid()) -> Symbol

Returns the specified thread's threadpool; either `:default`, `:interactive`, or `:foreign`.
"""
function threadpool(tid = threadid())
    tpid = ccall(:jl_threadpoolid, Int8, (Int16,), tid-1)
    return _tpid_to_sym(tpid)
end

"""
    Threads.nthreadpools() -> Int

Returns the number of threadpools currently configured.
"""
nthreadpools() = Int(unsafe_load(cglobal(:jl_n_threadpools, Cint)))

"""
    Threads.threadpoolsize(pool::Symbol = :default) -> Int

Get the number of threads available to the default thread pool (or to the
specified thread pool).

See also: `BLAS.get_num_threads` and `BLAS.set_num_threads` in the
[`LinearAlgebra`](@ref man-linalg) standard library, and `nprocs()` in the
[`Distributed`](@ref man-distributed) standard library.
"""
function threadpoolsize(pool::Symbol = :default)
    if pool === :default || pool === :interactive
        tpid = _sym_to_tpid(pool)
    elseif pool == :foreign
        error("Threadpool size of `:foreign` is indeterminant")
    else
        error("invalid threadpool specified")
    end
    return _nthreads_in_pool(tpid)
end

"""
    threadpooltids(pool::Symbol)

Returns a vector of IDs of threads in the given pool.
"""
function threadpooltids(pool::Symbol)
    ni = _nthreads_in_pool(Int8(0))
    if pool === :interactive
        return collect(1:ni)
    elseif pool === :default
        return collect(ni+1:ni+_nthreads_in_pool(Int8(1)))
    else
        error("invalid threadpool specified")
    end
end

"""
    Threads.ngcthreads() -> Int

Returns the number of GC threads currently configured.
This includes both mark threads and concurrent sweep threads.
"""
ngcthreads() = Int(unsafe_load(cglobal(:jl_n_gcthreads, Cint))) + 1

function threading_run(fun, static)
    ccall(:jl_enter_threaded_region, Cvoid, ())
    n = threadpoolsize()
    tid_offset = threadpoolsize(:interactive)
    tasks = Vector{Task}(undef, n)
    for i = 1:n
        t = Task(() -> fun(i)) # pass in tid
        t.sticky = static
        if static
            ccall(:jl_set_task_tid, Cint, (Any, Cint), t, tid_offset + i-1)
        else
            # TODO: this should be the current pool (except interactive) if there
            # are ever more than two pools.
            @assert ccall(:jl_set_task_threadpoolid, Cint, (Any, Int8), t, _sym_to_tpid(:default)) == 1
        end
        tasks[i] = t
        schedule(t)
    end
    for i = 1:n
        Base._wait(tasks[i])
    end
    ccall(:jl_exit_threaded_region, Cvoid, ())
    failed_tasks = filter!(istaskfailed, tasks)
    if !isempty(failed_tasks)
        throw(CompositeException(map(TaskFailedException, failed_tasks)))
    end
end

function _threadsfor(iter, lbody, schedule)
    lidx = iter.args[1]         # index
    range = iter.args[2]
    quote
        local threadsfor_fun
        let range = $(esc(range))
        function threadsfor_fun(tid = 1; onethread = false)
            r = range # Load into local variable
            lenr = length(r)
            # divide loop iterations among threads
            if onethread
                tid = 1
                len, rem = lenr, 0
            else
                len, rem = divrem(lenr, threadpoolsize())
            end
            # not enough iterations for all the threads?
            if len == 0
                if tid > rem
                    return
                end
                len, rem = 1, 0
            end
            # compute this thread's iterations
            f = firstindex(r) + ((tid-1) * len)
            l = f + len - 1
            # distribute remaining iterations evenly
            if rem > 0
                if tid <= rem
                    f = f + (tid-1)
                    l = l + tid
                else
                    f = f + rem
                    l = l + rem
                end
            end
            # run this thread's iterations
            for i = f:l
                local $(esc(lidx)) = @inbounds r[i]
                $(esc(lbody))
            end
        end
        end
        if $(schedule === :dynamic || schedule === :default)
            threading_run(threadsfor_fun, false)
        elseif ccall(:jl_in_threaded_region, Cint, ()) != 0 # :static
            error("`@threads :static` cannot be used concurrently or nested")
        else # :static
            threading_run(threadsfor_fun, true)
        end
        nothing
    end
end

"""
    Threads.@threads [schedule] for ... end

A macro to execute a `for` loop in parallel. The iteration space is distributed to
coarse-grained tasks. This policy can be specified by the `schedule` argument. The
execution of the loop waits for the evaluation of all iterations.

Tasks spawned by `@threads` are scheduled on the `:default` threadpool. This means that
`@threads` will not use threads from the `:interactive` threadpool, even if called from
the main thread or from a task in the interactive pool. The `:default` threadpool is
intended for compute-intensive parallel workloads.

See also: [`@spawn`](@ref Threads.@spawn) and
`pmap` in [`Distributed`](@ref man-distributed).
For more information on threadpools, see the chapter on [threadpools](@ref man-threadpools).

# Extended help

## Semantics

Unless stronger guarantees are specified by the scheduling option, the loop executed by
`@threads` macro have the following semantics.

The `@threads` macro executes the loop body in an unspecified order and potentially
concurrently. It does not specify the exact assignments of the tasks and the worker threads.
The assignments can be different for each execution. The loop body code (including any code
transitively called from it) must not make any assumptions about the distribution of
iterations to tasks or the worker thread in which they are executed. The loop body for each
iteration must be able to make forward progress independent of other iterations and be free
from data races. As such, invalid synchronizations across iterations may deadlock while
unsynchronized memory accesses may result in undefined behavior.

For example, the above conditions imply that:

- A lock taken in an iteration *must* be released within the same iteration.
- Communicating between iterations using blocking primitives like `Channel`s is incorrect.
- Write only to locations not shared across iterations (unless a lock or atomic operation is
  used).
- Unless the `:static` schedule is used, the value of [`threadid()`](@ref Threads.threadid)
  may change even within a single iteration. See [`Task Migration`](@ref man-task-migration).

## Schedulers

Without the scheduler argument, the exact scheduling is unspecified and varies across Julia
releases. Currently, `:dynamic` is used when the scheduler is not specified.

!!! compat "Julia 1.5"
    The `schedule` argument is available as of Julia 1.5.

### `:dynamic` (default)

`:dynamic` scheduler executes iterations dynamically to available worker threads. Current
implementation assumes that the workload for each iteration is uniform. However, this
assumption may be removed in the future.

This scheduling option is merely a hint to the underlying execution mechanism. However, a
few properties can be expected. The number of `Task`s used by `:dynamic` scheduler is
bounded by a small constant multiple of the number of available worker threads
([`Threads.threadpoolsize()`](@ref)). Each task processes contiguous regions of the
iteration space. Thus, `@threads :dynamic for x in xs; f(x); end` is typically more
efficient than `@sync for x in xs; @spawn f(x); end` if `length(xs)` is significantly
larger than the number of the worker threads and the run-time of `f(x)` is relatively
smaller than the cost of spawning and synchronizing a task (typically less than 10
microseconds).

!!! compat "Julia 1.8"
    The `:dynamic` option for the `schedule` argument is available and the default as of Julia 1.8.

### `:static`

`:static` scheduler creates one task per thread and divides the iterations equally among
them, assigning each task specifically to each thread. In particular, the value of
[`threadid()`](@ref Threads.threadid) is guaranteed to be constant within one iteration.
Specifying `:static` is an error if used from inside another `@threads` loop or from a
thread other than 1.

!!! note
    `:static` scheduling exists for supporting transition of code written before Julia 1.3.
    In newly written library functions, `:static` scheduling is discouraged because the
    functions using this option cannot be called from arbitrary worker threads.

## Example

To illustrate of the different scheduling strategies, consider the following function
`busywait` containing a non-yielding timed loop that runs for a given number of seconds.

```julia-repl
julia> function busywait(seconds)
            tstart = time_ns()
            while (time_ns() - tstart) / 1e9 < seconds
            end
        end

julia> @time begin
            Threads.@spawn busywait(5)
            Threads.@threads :static for i in 1:Threads.threadpoolsize()
                busywait(1)
            end
        end
6.003001 seconds (16.33 k allocations: 899.255 KiB, 0.25% compilation time)

julia> @time begin
            Threads.@spawn busywait(5)
            Threads.@threads :dynamic for i in 1:Threads.threadpoolsize()
                busywait(1)
            end
        end
2.012056 seconds (16.05 k allocations: 883.919 KiB, 0.66% compilation time)
```

The `:dynamic` example takes 2 seconds since one of the non-occupied threads is able
to run two of the 1-second iterations to complete the for loop.
"""
macro threads(args...)
    na = length(args)
    if na == 2
        sched, ex = args
        if sched isa QuoteNode
            sched = sched.value
        elseif sched isa Symbol
            # for now only allow quoted symbols
            sched = nothing
        end
        if sched !== :static && sched !== :dynamic
            throw(ArgumentError("unsupported schedule argument in @threads"))
        end
    elseif na == 1
        sched = :default
        ex = args[1]
    else
        throw(ArgumentError("wrong number of arguments in @threads"))
    end
    if !(isa(ex, Expr) && ex.head === :for)
        throw(ArgumentError("@threads requires a `for` loop expression"))
    end
    if !(ex.args[1] isa Expr && ex.args[1].head === :(=))
        throw(ArgumentError("nested outer loops are not currently supported by @threads"))
    end
    return _threadsfor(ex.args[1], ex.args[2], sched)
end

function _spawn_set_thrpool(t::Task, tp::Symbol)
    tpid = _sym_to_tpid(tp)
    if tpid == -1 || _nthreads_in_pool(tpid) == 0
        tpid = _sym_to_tpid(:default)
    end
    @assert ccall(:jl_set_task_threadpoolid, Cint, (Any, Int8), t, tpid) == 1
    nothing
end

"""
    Threads.@spawn [:default|:interactive] expr

Create a [`Task`](@ref) and [`schedule`](@ref) it to run on any available
thread in the specified threadpool (`:default` if unspecified). The task is
allocated to a thread once one becomes available. To wait for the task to
finish, call [`wait`](@ref) on the result of this macro, or call
[`fetch`](@ref) to wait and then obtain its return value.

Values can be interpolated into `@spawn` via `\$`, which copies the value
directly into the constructed underlying closure. This allows you to insert
the _value_ of a variable, isolating the asynchronous code from changes to
the variable's value in the current task.

!!! note
    The thread that the task runs on may change if the task yields, therefore `threadid()` should not
    be treated as constant for a task. See [`Task Migration`](@ref man-task-migration), and the broader
    [multi-threading](@ref man-multithreading) manual for further important caveats.
    See also the chapter on [threadpools](@ref man-threadpools).

!!! compat "Julia 1.3"
    This macro is available as of Julia 1.3.

!!! compat "Julia 1.4"
    Interpolating values via `\$` is available as of Julia 1.4.

!!! compat "Julia 1.9"
    A threadpool may be specified as of Julia 1.9.

# Examples
```julia-repl
julia> t() = println("Hello from ", Threads.threadid());

julia> tasks = fetch.([Threads.@spawn t() for i in 1:4]);
Hello from 1
Hello from 1
Hello from 3
Hello from 4
```
"""
macro spawn(args...)
    tp = QuoteNode(:default)
    na = length(args)
    if na == 2
        ttype, ex = args
        if ttype isa QuoteNode
            ttype = ttype.value
            if ttype !== :interactive && ttype !== :default
                throw(ArgumentError("unsupported threadpool in @spawn: $ttype"))
            end
            tp = QuoteNode(ttype)
        else
            tp = ttype
        end
    elseif na == 1
        ex = args[1]
    else
        throw(ArgumentError("wrong number of arguments in @spawn"))
    end

    letargs = Base._lift_one_interp!(ex)

    thunk = Base.replace_linenums!(:(()->($(esc(ex)))), __source__)
    var = esc(Base.sync_varname)
    quote
        let $(letargs...)
            local task = Task($thunk)
            task.sticky = false
            _spawn_set_thrpool(task, $(esc(tp)))
            if $(Expr(:islocal, var))
                put!($var, task)
            end
            schedule(task)
            task
        end
    end
end

# This is a stub that can be overloaded for downstream structures like `Channel`
function foreach end

# Scheduling traits that can be employed for downstream overloads
abstract type AbstractSchedule end
struct StaticSchedule <: AbstractSchedule end
struct FairSchedule <: AbstractSchedule end